Design of Pareto optimal _CO2 cap-and-trade policies for deregulated electricity networks

Among the _CO2 emission reduction programs, cap-and-trade (C&T) is one of the most used policies. Economic studies have shown that C&T policies for electricity networks, while reducing emissions, will likely increase price and decrease consumption of electricity. This paper presents a two layer mathematical-statistical model to develop Pareto optimal designs for _CO2 cap-and-trade policies. The bottom layer finds, for a given C&T policy, equilibrium bidding strategies of the competing generators while maximizing social welfare via a DC optimal power flow (DC-OPF) model. We refer to this layer as policy evaluation. The top layer (called policy optimization) involves design of Pareto optimal C&T policies over a planning horizon. The performance measures that are considered for the purpose of design are social welfare and the corresponding system marginal price (MP), _CO2 emissions, and electricity consumption level.